The Eckerson Group's Dave Wells and Cloudera's Eva Nahiri share the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Cloud data management CDM is simply data management that involves clouds. For example, when focused on data persistence, CDM provides cloud-native data storage and optimized processing for the burgeoning volumes of enterprise data, big data, and data from new sources that users are choosing to manage and use on clouds. When focused on integration, CDM provides data integration infrastructure (with related functions for quality and semantics) to unify multicloud and hybrid on-premises/cloud environments.
Getting insights from observability data such as logs and metrics is essential for managing cloud services reliably. However, managing massive observability data volumes can be expensive and complex. Luckily observability data pipelines can help IT handle large data volumes and reduce costs by processing, routing, and filtering data across teams, tools, and storage options. Should you build your own or buy?
TDWI research has found that organizations are increasingly modernizing their data warehouse environments. Often the current environment is not sufficient to support new analytics initiatives or they need to support new data types for analytics. Many enterprises are moving to the cloud as part of this journey. In fact, cloud data warehouses and cloud data lakes are already mainstream. The popularity of automated tools is growing as environments become more complex.